Many different types of data compression have been developed during the past half century to facilitate electronic data transmission and electronic data storage. Many data-compression methods are lossless, in that, absent errors, decompression of data compressed by lossless compression techniques returns the original data. Many other compression methods are referred to as “lossy,” because the methods obtain compression at the expense of loss of a portion of the original information content of the data that is compressed. Examples of lossless data compression include various types of entropy coding, including Huffman encoding and run-length encoding, which more efficiently encode the original data. Examples of lossy compression methods include the quantization of discrete-cosine-transform coefficients and resolution-decimation steps undertaken in MPEG compression of video signals. Compression methods can be characterized by a compression ratio achieved by applying the compression methods, where the compression ratio is the size of the compressed data produced by applying a compression method to initial or input data divided by the size of the initial or input data
Many of the well-known data-compression techniques are oriented to compressing a given, initial amount of data or a data stream from a single data source. These compression techniques generally seek to identify and remove redundant data from a given signal or stream and/or to remove unneeded information from the data set or data stream. The emergence of distributed, networked systems of computers and other electronic components has been accompanied by efforts to further decrease compression ratios in order to decrease data-transmission overheads and delays and to obtain higher data throughput through bandwidth-limited transmission media.